Objectives

• How to use regression in machine learning which consists of mathematical methods that allow you to predict a continuous outcome (y) based on the value of one or more predictor variables (x) • how to study your data to extract meaningful insights for business• how to prepare your data for forecasting• How to use regression in machine learning which consists of mathematical methods that allow you to predict a continuous outcome based on the value of one or more predictor

Outcomes

• Make accurate predictions.• Make precise data forecasts.• Make powerful analyses for data.• Extract meaningful insights for business from data.• Have a strong understanding of many Machine Learning Regression algorithms.• Make powerful analysis.• Add significant worth to your business.• Create strong added value to your business.• Employ Machine Learning for personal gain.• Know which Machine Learning model to choose for each type of problem.• Build an army of powerful Machine Learning models and know how to combine them to solve any problem.

Course Contents

• What is data prediction.• Difference between data science and data analysis• What is machine learning and its parts.• How to get data • Prepare data for prediction and analysis using data preprocessing. • Learn how to deal with missing data and categorical data.• Learn how to relates a dependent variable to one or more independent (explanatory) variables using regression. • Types of regression:o Simple Linear Regressiono Multiple Linear Regressiono Polynomial Regressiono SVR, Decision Tree Regressiono Random Forest Regression• How to evaluate and select best model for our data • Performance analysis

Description

Data will be available soon!